Dataflow Analysis of Serverless Scientific Applications using Provenance Data - Ribeiro, Marcello W. M.; de Paula, Ubiratam; Kunstmann, Liliane; Frota, Yuri; Rosseti, Isabel; de Oliveira, Daniel (Anais do Simpósio Brasileiro de Banco de Dados (SBBD); 2025: Anais do XL Simpósio Brasileiro de Bancos de Dados, 2025)
This paper presents an approach to ease dataflow analysis in Computational Science and Engineering (CSE) applications that invoke serverless functions. By capturing provenance data while executing CSE applications within a serverless environment, the approach organizes this information into an integrated database that users can query at runtime. Since serverless platforms typically lack native support for provenance tracking, the proposed solution helps users understand and analyze the behavior and outcomes of their CSE applications. We detail the main features of the approach as implemented in the DENETHOR tool and evaluate its effectiveness with a real-world CSE application. The results demonstrate that DENETHOR enhances analytical capabilities via its provenance database.